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Emotion Recognition in Speech: This project leverages advanced machine learning techniques to classify emotions from speech using the Toronto Emotional Speech Set (TESS). By extracting Mel-Frequency Cepstral Coefficients (MFCC) and utilizing an LSTM-based deep learning model, the project accurately identifies emotions like anger, happiness, and sad
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